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October 11, 2025Information Technology And ControlOpen Access

Forest Fire Recognition and Prediction Based on Fully Convolutional Network and Rothermel Model

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Authors

MCMingyi ChenKSKang ShiYTYuxin Tan

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Overview

Combining FCN and Rothermel model improves fire recognition and prediction accuracy in forest environments.

Key Points

  • The combined model significantly enhances fire recognition and prediction accuracy, improving decision-making.
  • Rothermel model achieves 87% accuracy and 70.9% stability in predicting fire spread patterns.
  • The innovative use of fully convolutional networks allows for effective segmentation of fire stages.
  • Integrating drone technology may advance smart fire prevention strategies and improve field responses.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/68e9b2e4ba7d64b6fc13315chttps://doi.org/10.5755/j01.itc.54.3.41742
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  5. 5Optimizing a Fire and Smoke Detection System Model with Hyperparameter Tuning and Callback on Forest Fire Images Using ConvNet Algorithm2024